What you can do with Google BigQuery
Perform high-performance CRUD operations on your relational data
Query and manipulate structured as well as unstructured data without any hassle
Build modern, data-driven applications with support for microservices and many DevOps-friendly tools
Extend the capabilities of PostgreSQL to work with time series data, spatial data, as well as graphs
Read from and write to various external data sources including MongoDB, MySQL, Oracle, Redis, and more
Setting up a BigQuery data warehouse on your own can be quite exhausting and time-consuming. You have to build and maintain the data warehouse from scratch, in addition to defining the schema that determines how the data from the sources gets stored in the warehouse.
By simply connecting BigQuery as a destination in RudderStack, you can get started in no time at all.
How to set up Google the BigQuery Integration
It’s very easy! Use our step-by-step guide to set up BigQuery as a destination in RudderStack, and get started in no time at all.
Collect, Store, and Analyze Your Event Data with Lightning-fast Speed Using RudderStack and Google BigQuery
RudderStack supports sending your event data from a variety of sources to Google BigQuery. Once you add BigQuery as a destination in RudderStack, all your event data is stored into BigQuery buckets periodically. With RudderStack, you don’t have to worry about defining a warehouse schema either – it will take care of everything.
By Integrating BigQuery Support with RudderStack, you can:
- Directly send your event data from a variety of sources, including web and mobile
- Load data into BigQuery without having to define a warehouse schema
- Get the data already transformed and ready for analytics
- Focus solely getting relevant business insights out of your data rather worrying about storing and retrieving it
How can we help you?
Google BigQuery is a GCP data warehouse that enables developers to send data from their Data Warehouse.
Difficulty can vary based on your data structure, data cleanliness and required destinations. Many users choose to simplify implementation by sending warehouse data through secure GCP data warehouse integration tools like RudderStack.
Pricing for Google BigQuery can vary depending on your use case and data volume. RudderStack offers transparent, volume-based event pricing. See RudderStack's pricing.
Google BigQuery is a web service offering from Google used for handling and analyzing Big Data. As a part of the Google Cloud Platform, BigQuery allows you to manage large amounts of data and perform real time analysis using SQL-like queries. BigQuery follows the principle of NoOps (No Operations), a concept which implies there is no need for a dedicated team to manage the tool.
Google BigQuery is a managed data warehouse. This means that you can access the data stored in BigQuery by using SQL queries. BigQuery self-manages the storage, encryption, scaling and performance management aspects of your data.
BigQuery is a REST-based web service. It allows you to run complex analytical queries for large amounts of data using SQL. BigQuery is not a substitute for a traditional relational database. It is primarily used for running analytical queries, and not for simple CRUD operations or queries.
BigQuery is built using the Google Dremel paper, which is also an inspiration for other popular tools such as Apache Drill, Apache Impala, and Dremio. Dremel is Google’s distributed system used for interactive querying of large datasets. It is capable of running queries over trillions of rows in seconds.